# From CERN 19,166 courses and talks. - [Thermalization Under Generalized Symmetries](https://invisiblenetwork.ai/learn/cern/3025680): Joao C. Pinto Barros · CERN - [Bubble nucleation in long-range systems](https://invisiblenetwork.ai/learn/cern/3025696): Laura Batini · CERN - [False vacuum decay in quantum spin chains and quantum simulators](https://invisiblenetwork.ai/learn/cern/3025669): Gianluca Lagnese · CERN - [Ergodicity-breaking scenarios in quantum link lattice gauge theories](https://invisiblenetwork.ai/learn/cern/3025670): Debasish Banerjee · CERN - [Color Glass to Color Fluid: Thermalization in ultrarelativistic heavy-ion collisions](https://invisiblenetwork.ai/learn/cern/3025664): Raju Mr Venugopalan · CERN - [The promise of Simulation-based inference for the dark sector](https://invisiblenetwork.ai/learn/cern/3025668): Roberto Trotta · CERN - [New ideas for nonthermal fixed points](https://invisiblenetwork.ai/learn/cern/3025671): Michal Heller · CERN - [From phase space to Krylov space: complexity and the geometry of chaos](https://invisiblenetwork.ai/learn/cern/3025662): Julian Sonner · CERN - [Emergent spacetime geometry for quantum matter](https://invisiblenetwork.ai/learn/cern/3025656): Stefan Floerchinger · CERN - [Hydrodynamic attractors in ultracold atoms](https://invisiblenetwork.ai/learn/cern/3025655): Tilman Enss · CERN - [Evidence of different prompt $\Lambda_c^+$ baryon and D meson elliptic flow in Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.36 TeV with ALICE at the LHC](https://invisiblenetwork.ai/learn/cern/3025657): Stefano Politano · CERN - [From projected to observable-projected ensembles](https://invisiblenetwork.ai/learn/cern/3025659): Sara Murciano · CERN - [Lessons from Spec-Driven Development](https://invisiblenetwork.ai/learn/cern/3025661): Simon Martinelli · CERN - [Regular Black Holes and Black Hole Mimickers: What Are They and How To Find Them](https://invisiblenetwork.ai/learn/cern/3025660): Stefano Liberati · CERN - [Non-ergodic dynamics in SU(2) lattice gauge theory: scars, fragmentation, and disorder-free localization](https://invisiblenetwork.ai/learn/cern/3025647): Giovanni Cataldi · CERN - [Quasiparticle wavepackets for glueball scattering on a qutrit chain](https://invisiblenetwork.ai/learn/cern/3025646): Marco Rigobello · CERN - [Welcome](https://invisiblenetwork.ai/learn/cern/3025645): Enrique Rico Ortega · CERN - [Group Invariant Quantum Many-Body Scars and Unconventional Electron Pairing](https://invisiblenetwork.ai/learn/cern/3025651): Kiryl Pakrouski · CERN - [GWEEP: A Deep Learning Toolkit for Low‑Latency Gravitational‑Wave Analysis](https://invisiblenetwork.ai/learn/cern/3025638): Ana Caramete · CERN - [★ Normalizing flows for complete parameter estimation on time-frequency representations of gravitational-wave data ★](https://invisiblenetwork.ai/learn/cern/3025640): Daniel Lanchares · CERN - [★ Scalable detection of long-duration gravitational wave signals from neutron star binaries in next-generation ground-based detectors ★](https://invisiblenetwork.ai/learn/cern/3025642): Martin Gerini · CERN - [The Present and the Future of Machine Learning for Multi-Messenger Astrophysics](https://invisiblenetwork.ai/learn/cern/3025639): Michael Coughlin · CERN - [The Political Economy of Compute: Provocations and Pathways](https://invisiblenetwork.ai/learn/cern/3025637): Jo Walton · CERN - [Deployable Reinforcement Learning for Interferometric Control](https://invisiblenetwork.ai/learn/cern/3025643): Nikhil Mukund · CERN - [GlitchFlow: generative neural networks for de-noising gravitaional waves data in present and future detectors.](https://invisiblenetwork.ai/learn/cern/3025649): Francesco Sarandrea · CERN - [Operations of GW alert validation in O4](https://invisiblenetwork.ai/learn/cern/3025644): Sarah ANTIER · CERN - [★ BOAW: a neural network approach to combining multiple pipelines in gravitational-wave searches ★](https://invisiblenetwork.ai/learn/cern/3025641): Nikolas Moustakidis and Theofilos Moustakidis · CERN - [Wattnet: High-Resolution Carbon and Water Intensity Modelling to Enable Impact-Aware Research Computing.](https://invisiblenetwork.ai/learn/cern/3025602): JAIME IGLESIAS BLANCO · CERN - [Adaptive Infrastructure and Efficiency Strategies at a GridKa WLCG Tier-1 Center](https://invisiblenetwork.ai/learn/cern/3025606): Lars Sowa · CERN - [An Energy-Efficient Data Centre with Heat recovery at Queen Mary University of London \[Online\]](https://invisiblenetwork.ai/learn/cern/3025603): Sudha Ahuja · CERN - [GreenMetaData: Standardising Environmental Impact Reporting for Computational Research \[Online\]](https://invisiblenetwork.ai/learn/cern/3025614): Jyoti Bhogal · CERN - [Modelling Scenarios for Carbon-aware Geographic Load Shifting of Compute Workloads \[Online\]](https://invisiblenetwork.ai/learn/cern/3025622): Wim Vanderbauwhede · CERN - [On the Challenges in Assessing the Sustainability of AI \[Online\]](https://invisiblenetwork.ai/learn/cern/3025616): Raghavendra Selvan · CERN - [Environmentally Sustainable HeAlth REsearch (SHARE) Considerations of ethics, justice, responsibility and reflexivity.](https://invisiblenetwork.ai/learn/cern/3025621): Gabby Samuel · CERN - [SUSFECIT: Objectives and Concepts](https://invisiblenetwork.ai/learn/cern/3025619): Dwayne Spiteri · CERN - [Enhancing Sustainable Research: A holistic Approach to Sustainable Computing](https://invisiblenetwork.ai/learn/cern/3025618): Georgios Sarantakos and Xavier Eric Ouvrard · CERN - [Using co-design to improve computing carbon calculators](https://invisiblenetwork.ai/learn/cern/3025617): Christina Bremer · CERN - [The One Token Model: A Multi-Layer Framework for the Granular Estimation of AI Inference Energy](https://invisiblenetwork.ai/learn/cern/3025615): Mathieu Francois · CERN - [Optimizing Energy Efficiency at the WLCG PIC Tier-1: From Predictive Job Scheduling to Real-Time CPU Control](https://invisiblenetwork.ai/learn/cern/3025620): Jose Flix Molina · CERN - [★ GWAK2: Gravitational Wave Anomalous Knowledge using SSL ★](https://invisiblenetwork.ai/learn/cern/3025623): Andy Chen and Eric Anton Moreno · CERN - [★ From Inspiral to Inference: BNS Parameter Estimation with State Space Models ★](https://invisiblenetwork.ai/learn/cern/3025625): Kyungseop Yoon · CERN - [Deep Loop Shaping for Angular Sensing and Control in Virgo](https://invisiblenetwork.ai/learn/cern/3025633): Tomislav Andric · CERN - [Tools for real-time inferences in GW detectors](https://invisiblenetwork.ai/learn/cern/3025629): Sebastien Viret · CERN - [From Post Hoc Subtraction to Source Suppression: ML Noise Mitigation in Advanced LIGO](https://invisiblenetwork.ai/learn/cern/3025626): Christina Reissel · CERN - [★ SlotFlow: Amortized Trans-Dimensional Inference towards LISA ★](https://invisiblenetwork.ai/learn/cern/3025624): Giovanni Giarda · CERN - [★ Linear Oscillatory State-Space Models for Binary Neutron Star Detection ★](https://invisiblenetwork.ai/learn/cern/3025628): Benedict Armstrong · CERN - [The CERN AI infrastructure](https://invisiblenetwork.ai/learn/cern/3025632): Ricardo Rocha · CERN - [AI on edge, underground and in space](https://invisiblenetwork.ai/learn/cern/3025631): Sioni Paris Summers · CERN [Next page](https://invisiblenetwork.ai/learn/browse?source=cern&page=353)